Statistical Modelling in R

Statistical Modelling in R

by Murray Aitkin, Ross Darnell, Brian Francis, John Hinde
     
 

R is now the most widely used statistical package/language in university statistics departments and many research organisations. Its great advantages are that it is now the leading-edge statistical package/language and that it can be freely downloaded from the R website. Its cooperative development and open code also attract many contributors which means that the… See more details below

Overview

R is now the most widely used statistical package/language in university statistics departments and many research organisations. Its great advantages are that it is now the leading-edge statistical package/language and that it can be freely downloaded from the R website. Its cooperative development and open code also attract many contributors which means that the modelling and data analysis possibilities in R are much richer than in GLIM4, and so the R edition can be substantially more comprehensive than the GLIM4 edition of Statistical Modelling.

Product Details

ISBN-13:
9780199219131
Publisher:
Oxford University Press, USA
Publication date:
03/29/2009
Pages:
568
Product dimensions:
6.10(w) x 9.20(h) x 1.30(d)

Table of Contents

1 Introducing R 1

2 Statistical modelling and inference 28

3 Regression and analysis of variance 97

4 Binary response data 195

5 Multinomial and Poisson response data 269

6 Survival data 347

7 Finite mixture models 433

8 Random effect models 461

9 Variance component models 508

Bibliography 554

R function and constant index 567

Dataset index 570

Subject index 571

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